Missing data analysis with fuzzy C-Means: A study of its application in a psychological scenario-Reference-Cited by-同舟云学术

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Missing data analysis with fuzzy C-Means: A study of its application in a psychological scenario

Published:2011-06 Issue:6 Volume:38 Page:6793-6797
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Di Nuovo Alessandro G.

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference22 articles.

1. Missing data;Allison,2001

2. Diagnostic statistic manual, text revised (DSM-IV-TR);APA,2000

3. Pattern recognition with fuzzy objective function algorithms;Bezdek,1981

4. Fuzzy Models and algorithms for pattern recognition and image processing;Bezdek,1999

5. Statistical power analysis for the behavioral sciences;Cohen,1988

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1. RETRACTED: LIKFCM: Linear interpolation-based kernelized fuzzy C-means clustering imputation method for handling incomplete data;Journal of Intelligent & Fuzzy Systems;2024-02-14

2. Revolutionizing Missing Data Handling with RFKFCM: Random Forest-based Kernelized Fuzzy C-Means;Procedia Computer Science;2024

3. LIPFCM: Linear Interpolation-Based Possibilistic Fuzzy C-Means Clustering Imputation Method for Handling Incomplete Data;Proceedings of Data Analytics and Management;2023

4. Handling Missing Values Using Fuzzy Clustering: A Review;Advances in Intelligent Systems and Computing;2023

5. Attention-Based Sequence-to-Sequence Model for Time Series Imputation;Entropy;2022-12-09

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